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Frontiers of Information Technology & Electronic Engineering  2019 Vol.20 No.1 P.76-87

http://doi.org/10.1631/FITEE.1800557


Time-varying formation tracking for uncertain second-order nonlinear multi-agent systems


Author(s):  Mao-peng Ran, Li-hua Xie, Jun-cheng Li

Affiliation(s):  School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore 639798, Singapore

Corresponding email(s):   mpran@ntu.edu.sg, ELHXIE@ntu.edu.sg, juncheng001@e.ntu.edu.sg

Key Words:  Multi-agent system, Time-varying formation, Formation tracking, Nonlinear dynamics, Extended state observer (ESO)


Mao-peng Ran, Li-hua Xie, Jun-cheng Li. Time-varying formation tracking for uncertain second-order nonlinear multi-agent systems[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(1): 76-87.

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journal="Frontiers of Information Technology & Electronic Engineering",
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publisher="Zhejiang University Press & Springer",
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%A Jun-cheng Li
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T1 - Time-varying formation tracking for uncertain second-order nonlinear multi-agent systems
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Abstract: 
Our study is concerned with the time-varying formation tracking problem for second-order multi-agent systems that are subject to unknown nonlinear dynamics and external disturbance, and the states of the followers form a predefined time-varying formation while tracking the state of the leader. The total uncertainty lumps the unknown nonlinear dynamics and the external disturbance, and is regarded as an extended state of the agent. To estimate the total uncertainty, we design an extended state observer (ESO). Then we propose a novel ESO based time-varying formation tracking protocol. It is proved that, under the proposed protocol, the ESO estimation error and the time-varying formation tracking error can be made arbitrarily small. An application to the target enclosing problem for multiple unmanned aerial vehicles (UAVs) verifies the effectiveness and superiority of the proposed approach.

不确定二阶非线性多智能体系统时变编队跟踪控制

摘要:研究了含未知非线性动态和外界干扰的二阶多智能体系统时变编队跟踪控制问题。在所考虑的时变编队跟踪控制中,每个跟踪者在完成预设编队的同时,需要跟踪领导者轨迹。将未知非线性动态和外界干扰视为每个多智能体的扩张状态,并设计扩张状态观测器对扩张状态进行在线观测。在此基础上,提出基于扩张状态观测器的时变编队跟踪控制协议。理论分析表明,所设计的时变编队跟踪控制协议能够保证观测器观测误差和多智能体系统时变编队跟踪误差收敛至任意小。最后,将所设计的时变编队跟踪协议应用于无人机目标合围问题,验证了该方法的有效性。

关键词:多智能体系统;时变编队;编队跟踪;非线性动态;扩张状态观测器

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Bechlioulis CP, Rovithakis GA, 2017. Decentralized robust synchronization of unknown high order nonlinear multi-agent systems with prescribed transient and steady state performance. IEEE Trans Autom Contr, 62(1):123-134.

[2]Castañeda LA, Luviano-Juárez A, Chairez I, 2015. Robust trajectory tracking of a delta robot through adaptive active disturbance rejection control. IEEE Trans Contr Syst Technol, 23(4):1387-1398.

[3]Chang XY, Li YL, Zhang WY, et al., 2015. Active disturbance rejection control for a flywheel energy storage system. IEEE Trans Ind Electron, 62(2):991-1001.

[4]Chen LM, Li CJ, Mei J, et al., 2017. Adaptive cooperative formation-containment control for networked Euler-Lagrange systems without using relative velocity information. emphIET Contr Theory Appl, 11(9):1450-1458.

[5]Chen YY, Wang ZZ, Zhang Y, et al., 2017a. A geometric extension design for spherical formation tracking control of second-order agents in unknown spatiotemporal flowfields. emphNonl Dynam, 88(2):1173-1186.

[6]Chen YY, Zhang Y, Wang ZZ, 2017b. An adaptive backstepping design for formation tracking motion in an unknown Eulerian specification flowfield. emphJ Franklin Inst, 354(14):6217-6233.

[7]Cui RX, Ge SS, How BVE, et al., 2010. Leader-follower formation control of underactuated autonomous underwater vehicles. emphOcean Eng, 37(17-18):1491-1502.

[8]Dong XW, Yu BC, Shi ZY, et al., 2015. Time-varying formation control for unmanned aerial vehicles: theories and applications. emphIEEE Trans Contr Syst Technol, 23(1):340-348.

[9]Dong XW, Xiang J, Han L, et al., 2017a. Distributed time-varying formation tracking analysis and design for second-order multi-agent systems. emphJ Intell Robot Syst, 86(2):277-289.

[10]Dong XW, Zhou Y, Ren Z, et al., 2017b. Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying. emphIEEE Trans Ind Electron, 64(6):5014-5024.

[11]Du HB, Cheng MZQ, Wen GH, 2016. Leader-following attitude consensus for spacecraft formation with rigid and flexible spacecraft. emphJ Guid Contr Dynam, 39(4):944-951.

[12]Freidovich LB, Khalil HK, 2008. Performance recovery of feedback-linearization-based designs. emphIEEE Trans Autom Contr, 53(10):2324-2334.

[13]Galzi D, Shtessel Y, 2006. UAV formations control using high order sliding modes. American Control Conf, p.4249-4254.

[14]Guo BZ, Zhao ZL, 2011. On the convergence of an extended state observer for nonlinear systems with uncertainty. emphSyst Contr Lett, 60(6):420-430.

[15]Guo J, Yan GF, Lin ZY, 2010. Local control strategy for moving-target-enclosing under dynamically changing network topology. emphSyst Contr Lett, 59(10):654-661.

[16]Han JQ, 2009. From PID to active disturbance rejection control. emphIEEE Trans Ind Electron, 56(3):900-906.

[17]Herbst G, 2016. Practical active disturbance rejection control: bumpless transfer, rate limitation, and incremental algorithm. emphIEEE Trans Ind Electron, 63(3):1754-1762.

[18]Hu WH, Camacho EF, Xie LH, 2018. Output feedback control based on state and disturbance estimation. https://arxiv.org/abs/1801.06058

[19]Isidori A, 1989. Nonlinear Control Systems. Springer-Verlag Berlin Heidelberg.

[20]Jiang TT, Huang CD, Guo L, 2015. Control of uncertain nonlinear systems based on observers and estimators. emphAutomatica, 59:35-47.

[21]Khalil HK, 2002. Nonlinear Systems (3rd Ed.). Prentice Hall, New Jersey, USA.

[22]Leonard NE, Paley DA, Davis RE, et al., 2010. Coordinated control of an underwater glider fleet in an adaptive ocean sampling field experiment in Monterey Bay. emphJ Field Robot, 27(6):718-740.

[23]Li CJ, Chen LM, Guo YN, et al., 2018. Formation-containment control for networked Euler-Lagrange systems with input saturation. emphNonl Dynam, 91(2):1307-1320.

[24]Li SB, Zhang J, Li XL, et al., 2017. Formation control of heterogeneous discrete-time nonlinear multi-agent systems with uncertainties. emphIEEE Trans Ind Electron, 64(6):4730-4740.

[25]Li XX, Xie LH, 2018. Dynamic formation control over directed networks using graphical Laplacian approach. emphIEEE Trans Autom Contr, 63(11):3761-3774.

[26]Li ZK, Wen GH, Duan ZS, et al., 2015. Designing fully distributed consensus protocols for linear multi-agent systems with directed graphs. emphIEEE Trans Autom Contr, 60(4):1152-1157.

[27]Liao F, Teo R, Wang JL, et al., 2017. Distributed formation and reconfiguration control of VTOL UAVs. emphIEEE Trans Contr Syst Technol, 25(1):270-277.

[28]Lin ZY, Ding W, Yan GF, et al., 2013. Leader-follower formation via complex Laplacian. emphAutomatica, 49(6):1900-1906.

[29]Liu Y, Jia YM, 2012. An iterative learning approach to formation control of multi-agent systems. emphSyst Contr Lett, 61(1):148-154.

[30]Lotfi N, Zomorodi H, Landers RG, 2016. Active disturbance rejection control for voltage stabilization in open-cathode fuel cells through temperature regulation. emphContr Eng Pract, 56:92-100.

[31]Lü J, Chen F, Chen GR, 2016. Nonsmooth leader-following formation control of nonidentical multi-agent systems with directed communication topologies. emphAutomatica, 64:112-120.

[32]Meng DY, Jia YM, Du JP, et al., 2014. On iterative learning algorithms for the formation control of nonlinear multi-agent systems. emphAutomaitca, 50(1):291-295.

[33]Meng ZY, Ren W, You Z, 2010. Distributed finite-time attitude containment control for multiple rigid bodies. emphAutomatica, 46(12):2092-2099.

[34]Oh KK, Ahn HS, 2014. Formation control and network localization via orientation alignment. emphIEEE Trans Autom Contr, 59(2):540-545.

[35]Oh KK, Park MC, Ahn HS, 2015. A survey of multi-agent formation control. emphAutomatica, 53:424-440.

[36]Peng ZH, Wang D, Chen ZY, et al., 2013. Adaptive dynamic surface control for formations of autonomous surface vehicles with uncertain dynamics. emphIEEE Trans Contr Syst Technol, 21(2):513-520.

[37]Ran MP, Wang Q, Dong CY, et al., 2017a. Backstepping active disturbance rejection control: a delayed activation approach. emphIET Contr Theory Appl, 11(14):2336-2342.

[38]Ran MP, Wang Q, Dong CY, 2017b. Active disturbance rejection control for uncertain nonaffine-in-control nonlinear systems. emphIEEE Trans Autom Contr, 62(11):5830-5836.

[39]Ren W, 2007. Consensus strategies for cooperative control of vehicle formations. emphIET Contr Theory Appl, 1(2):505-512.

[40]Ren W, Sorensen N, 2008. Distributed coordination architecture for multi-robot formation control. emphRobot Auton Syst, 56(4):324-333.

[41]Wang JN, Xin M, 2013. Integrated optimal formation control of multiple unmanned aerial vehicles. emphIEEE Trans Contr Syst Technol, 21(5):1731-1744.

[42]Wang Q, Ran MP, Dong CY, 2016. Robust partial integrated guidance and control for missiles via extended state observer. emphISA Trans, 65:27-36.

[43]Wang XH, Yadav V, Balakrishnan SN, 2007. Cooperative UAV formation flying with obstacle/collision avoidance. emphIEEE Trans Contr Syst Technol, 15(4):672-679.

[44]Yang AL, Naeem W, Irwin GW, et al., 2014. Stability analysis and implementation of a decentralized formation control strategy for unmanned vehicles. emphIEEE Trans Contr Syst Technol, 22(2):706-720.

[45]Zhang HW, Lewis FL, 2012. Adaptive cooperative tracking control of higher-order nonlinear systems with unknown dynamics. emphAutomatica, 48(7):1432-1439.

[46]Zheng Q, Gao LQ, Gao ZQ, 2012. On validation of extended state observer through analysis and experimentation. emphJ Dynam Syst Meas Contr, 134(2):024505.

[47]Zhu B, Zaini AHB, Xie LH, 2017. Distributed guidance for interception by using multiple rotary-wing unmanned aerial vehicles. emphIEEE Trans Ind Electron, 64(7):5648-5656.

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